1. Field of the Invention
The present invention relates to a sleep state estimating device which estimates a sleep state based on vital signs information, and to a program product for executing a sleep state estimation function.
2. Description of the Related Art
Recently heightened health consciousness among people has created a desire to manage their health by day-to-day sleep control in their household.
During sleep, a person experiences various states through a night. The sleep is divided broadly into two types, namely, REM sleep and non-REM (NREM) sleep. The fact that the NREM sleep alternates with the REM sleep periodically several times during the sleep is known. In general, the sleep undergoes transition as follows. That is, a sleep state during the NREM sleep gradually transits from the light sleep to the deep sleep. After a predetermined duration of the deep sleep state, the sleep state moves toward the light sleep, resulting in the transition to the REM sleep. A finer sleep classification is Sleep Stage. Sleep Stage is regulated by an international standard, and consists of “REM sleep”, “Sleep Stages 1, 2, 3, and 4” and, “wakefulness”, the “Sleep Stages 1, 2, 3, and 4” being corresponding to the NREM sleep.
Up to now, various methods have been attempted to detect a change in sleep stage. Known examples thereof include polysomnography (PSG) in which electroencephalogram (EEG), electro-oculogram (EOG), electromyogram (EMG), and the like are detected to judge the sleep stage from the waveforms detected. However, the polysomnography requires a large-scale apparatus and can be used only at a site provided with measurement facilities such as a hospital, thereby being unsuitable for daily use such as use in fitness equipment. In addition, the polysomnography can be used for judgment only by a qualified person, and it is not sufficient only that a suitable apparatus is available.
Therefore, it is demanded to detect the change in sleep state with precision by means replacing the polysomnography. Known examples of a method for estimating a sleep stage without using the polysomnography include a method of estimating the sleep stage by applying a neural network theory, a chaos theory, or by using actual measurement data on sleep to measurements of respiration rate, heart rate, and body movement. Those methods for estimation are described in JP 09-294731 A and JP 2001-61820 A, and on pages 581-589 in Vol. 138, No. 7 of collected papers (or Proceedings) published by The Society of Instrument and Control Engineers in 2002.
However, the above-described sleep estimation according to prior art has a problem with a low probability of matching the actual change in sleep state, and much lower accuracy than the polysomnography in judging the deep sleep and the light sleep.
Further, in general, electrocardiogram is used to measure heart rate with precision. Measurement by the electrocardiogram, however, has a drawback in that plural electrodes have to be attached directly to the skin of a subject, restraining the body of a person with the cords extending from each electrode to the measurement equipment. On the other hand, a non-restraining sensor can only catch minute heart rate signals full of noises due to other elements than heartbeat. Non-restraining measurement therefore needs FFT and filter computation processing for frequency analysis as well as signal amplification processing, which complicate the measurement process.